XSS attack risk analysis method and device based on Bayesian network model

Abstract

The invention relates to an XSS attack risk analysis method and device based on a Bayesian network model. According to the method, a Bayesian network is used for directly constructing a network structure part of an XSS attack risk analysis model, prior probabilities of nodes in the Bayesian network model are obtained according to expert experience, a conditional probability table of the nodes is obtained through learning, and the complete XSS attack risk analysis model is obtained. In the XSS attack risk analysis model, through Bayesian network reasoning, the risk that a network system suffers from XSS attacks can be quantitatively analyzed, and a corresponding risk analysis result is obtained. According to the method, the XSS attack risk analysis model is constructed on the basis of the STRIDE threat model based on a network component and network data stream transmission relationship, so that the risk of the network suffering from the XSS attack can be quantitatively analyzed, the weak link in the network security protection can be found, and good data support can be provided for the formulation of a network defense strategy.

Description

technical field [0001] The present application relates to the technical field of network security, in particular to a Bayesian network model-based XSS attack risk analysis method and device. Background technique [0002] Over the past two decades, modern society's reliance on web applications has increased dramatically. Among all kinds of Web attacks, Cross Site Scripting (XSS) is a relatively common type of attack. Many information systems are based on B / S architecture and involve browsers. The risk of being attacked by XSS is very high. High, an XSS attack may cause greater harm. [0003] At present, the defense method for XSS attacks is mainly to filter the keywords of the input information on the server and the client, but this method has a high rate of false positives, and cannot protect the network system in time, and when facing more complex network attacks Basically helpless. At the same time, some researchers have used machine learning algorithms to detect XSS at...

AI Technical Summary

Problems solved by technology

Among all kinds of Web attacks, Cross Site Scripting (XSS) is a relatively common type of attack. Many information systems are based on B / S architecture and involve browsers. The risk of being attacked by XSS is very high. High, one XSS attack may cause greater harm

[0003] At present, the defense method for XSS attacks is mainly to filter the keywords of the input information on the server and the client, but this method has a high rate of false positives and cannot protect the network system in time, and in the face of more complex network attacks basically powerless

At the same time, some researchers have used machine learning algorithms to detect XSS attacks and improve attack detection performance, but these methods cannot quantitatively analyze the threat risk of XSS attacks, and cannot well support subsequent defense decision-making activities

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